Automatic discrimination of grapevine (Vitis viniferaL.) clones using leaf hyperspectral imaging and partial least squares

Abstract

A worldwide innovative method to discriminate grapevine clones is presented. It is an alternative to ampelography, isozyme and DNA analysis. The spectra and their first and second derivatives of 201 bands in the visible and near-infrared wavelength range between 634 and 759 nm were used as inputs to a classifier created using partial least squares. The spectra were acquired in the laboratory for the adaxial side of the apical part of the main lobe of fully hydrated grapevine leaves. The classifier created allowed the separation of 100 leaves of the Cabernet Sauvignon (Vitis vinifera L.) variety into four clones, namely CS 15, CS 169, CS 685 and CS R5, comprising 25 leaves each. The percentages of leaves correctly classified for these clones were 98·2, 99·2, 100 and 97·8%, respectively, when the classifier input was the second derivative of the normalized spectra. These percentages were determined by Monte-Carlo cross-validation. With the new method proposed, each leaf of a given variety can be classified in a few seconds according to its clone in an environmentally friendly way.

Support Vector Machine and Artificial Neural Network Models for the Classification of Grapevine Varieties Using a Portable NIR Spectrophotometer

“…20 different grapevine varieties were classified with an overall correct classification percentage of 87.25% in a site-specific approach. Similar recent studies such as [ 13 ] or [ 14 ] also reached high percentages in varietal (93.53%) and clone (98.8%) discrimination. Nevertheless, in [ 13 ], hyperspectral imaging was conducted with a camera operating between 380 nm and 1028 nm under laboratory conditions on leaf discs.…”

“…Also, plant varietal discrimination has been accomplished using spectroscopy in crops such as wheat [ 8 ], bayberry [ 9 ], pear [ 10 ], tomato [ 11 ] and strawberry [ 12 ], using different organs. Recent studies have explored the use of leaf spectroscopy for grapevine varietal and clone identification using hyperspectral imaging under laboratory conditions throughout destructive methods [ 13 , 14 ]. Also, these works used partial least squares discriminant analysis (PLS-DA) for the training of the models.…”

Arbuscular Mycorrhizal Symbiosis as a Promising Resource for Improving Berry Quality in Grapevines Under Changing Environments

“…The asexual propagation of the grapevine varieties allows the appearance and accumulation of somatic mutations, which are the basis for the clonal selection, which leads to differences in vigor, berry and cluster weight, yield production, resistance to plagues and diseases or oenological potential ( Fernandes et al, 2015 ). One of the adaptive agronomic strategies to use in modern viticulture under the on-going climate change conditions is the selection of the best adapted rootstock and clones.…”

Hyperspectral Classification of Plants: A Review of Waveband Selection Generalisability

“…This has been driven by the increased availability of hyperspectral sensing from imaging spectrometers and field spectroradiometers, and increasing need from environmental conservation, agriculture, and forestry groups [1]. High classification accuracies, particularly at fine taxonomic units such as species, or even clones for grapevine varieties [2], has in some cases been enabled by hyperspectral observation [3]. Hyperspectral measurements have been…”